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Multimodal imaging in the differential diagnosis of glioma recurrence from treatment-related effects: A protocol for systematic review and network meta-analysis.

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机构: [1]Guangzhou University of Chinese Medicine, Guangzhou, China [2]Qionghai Hospital of traditional Chinese Medicine, Qionghai, Hainan Province, China [3]The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangdong Province Hospital of Chinese Medical, Guangzhou, China [4]International Experimental Central Nervous System Injury & Repair (IECNSIR), Department of Surgical Sciences, Anesthesiology & Intensive Care Medicine, Uppsala University Hospital, Uppsala University, Uppsala, Sweden
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关键词: Glioma Treatment-related effects Pseudoprogression Protocol Network meta-analysis

摘要:
Glioma is the most common malignant primary brain tumor and it will always recur. To date, various multimodal imaging including magnetic resonance imaging (MRI) and positron emission tomography computed tomography (PET/CT) was used to differentiate the diagnosis of true tumor recurrent (TuR) and treatment-related effects (TrE) in glioma patient but with no overall conclusion. In this study, SROC curve and Bayesian network meta-analysis will be used to conduct a comprehensive analysis of the results of different clinical reports, and assess the efficacy of multimodal imaging in difference TuR and TrE.To find more comprehensive information about the application of multimodal imaging in glioma patients, we searched the EMBASE, Pubmed, and Cochrane Central Register of Controlled Trials for relevant clinical trials. We also reviewed their reference lists to avoid omissions. QUADAS-2, RevMan software, Stata, and R software will be used.This study will provide reliable evidence for the efficacy of multimodal imaging in the differential diagnosis of TuR and TrE in glioma patients.We will evaluate the effectiveness of different and rank each imaging method in glioma patients to provide a decision-making reference on which method to choose for clinicians. Protocol registration number: CRD42020217861.Copyright © 2021 Elsevier B.V. All rights reserved.

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大类 | 3 区 医学
小类 | 4 区 神经科学
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Q4 NEUROSCIENCES
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第一作者机构: [1]Guangzhou University of Chinese Medicine, Guangzhou, China
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